A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Please consider using http://lygia.xyz instead of copy/pasting this functions. It expand suport for voronoi, voronoise, fbm, noise, worley, noise, derivatives and much more, through simple file dependencies. Take a look to https://github.com/patriciogonzalezvivo/lygia/tree/main/generative

float rand(float n){return fract(sin(n) * 43758.5453123);}

float noise(float p){
	float fl = floor(p);
  float fc = fract(p);

Standard escape codes are prefixed with Escape:

• Ctrl-Key: ^[
• Octal: \033
• Unicode: \u001b
• Hexadecimal: \x1B
• Decimal: 27

Every tool, technique, and idea from David Ondrej's interview with Thorsten Ball (Amp) — agents in orbs, the Oracle, Puck the meta-agent, the prompting playbook, and the features Amp killed on purpose.

Click here to view the Episode Pack

(It's a single self-contained HTML page — the file thorsten-episode-pack.html below. You can also download it and open it in any browser.)

A Claude Code Agent Skill built from Thorsten Ball's (Amp) playbook on David Ondrej's podcast.

"An agent has two sources of information: training data and the context window. That's it. The most important number in this equation is the information that you put in."

Most skills change what your agent does. This one changes what you do — it coaches you to prompt like a senior engineer briefing another senior engineer, and it gets quieter as you get better.